Summary
Marcell Nagy is a Senior Data Scientist with 7 years of experience and a PhD in network and data science, blending strong mathematical rigour with practical ML engineering across academia and industry. He has led applied research and R&D projects in anomaly detection, LLM-enabled systems (including RAG pipelines and semantic chunking), educational analytics, and medical AI, collaborating with partners like Nokia Bell Labs and Translational Medicine. Marcell has a track record of mentoring junior researchers, building production-facing tools (FastAPI, Streamlit), and contributing to curriculum and institute-level initiatives in health data science. His Fulbright research at Indiana University and work on the Human Reference Atlas highlight a rare intersection of network science and biomedical applications. Based in Madrid and currently at INSUS, he combines interpretability-first modeling with time-series and NLP expertise to turn complex, noisy data into actionable insights.
7 years of coding experience
8 years of employment as a software developer
Doctor of Philosophy - PhD, Network science and data science, 100% - summa cum laude, Doctor of Philosophy - PhD, Network science and data science, 100% - summa cum laude at Budapest University of Technology and Economics
Fulbright Visiting Student Researcher, Network Science & Data Science, Fulbright Visiting Student Researcher, Network Science & Data Science at Indiana University Bloomington